Video images are increasingly used in industrial applications for process monitoring and supervision and in video surveillance applications for public and private sites. These applications generally use a network of cameras carefully arranged so as to provide reliable images at different points of the monitored area. The images provided by the different cameras are compressed, then stored in a video database for later use. In most applications, in particular in the video surveillance field, this use requires that a large volume of video images be processed, in particular when the network includes a large number of cameras spread out over a large area, such as a town, for example. The quantity of stored images quickly becomes too large for an operator to be able to perform a quick and effective analysis of the images in order to extract the actions or objects that are relevant to the considered application.
In practice, an investigation may require viewing and/or processing several tens of thousands of hours of video. It is then difficult to find the desired information if no prior indexing of the videos was done upon acquisition. Furthermore, the videos available during the search are those that were stored, therefore compressed, and no longer have the optimal image quality for the richest possible extraction of information.
In the prior art, there are systems generating alarms on predefined events or indications. However, in some applications, the events and indications generating the alarms can be insufficient to quickly and effectively navigate through the archives looking for objects (individuals, vehicles) of a nature to provide relevant information. This is the case for example when looking for suspects in a crowd at various points of an area monitored by cameras.
One drawback of current video surveillance systems is related to the fact that they deal solely with current events and generate alarms for predefined events. The notion of “memory” of such a system is limited to the videos recorded and alarms detected.
The systems do not make it possible to find an event that did not generate an alarm when it occurred, but has become decisive in the context of a later investigation.
A first aim of the invention is to organize the memory of such systems so that they allow an effective investigation by limiting the amount of data to be analyzed by the operator, and by systematically annotating the streams of images obtained by the cameras in order to enable a quick selection of video sequences that are relevant for the investigation.
A second aim of the invention is to provide material tools and software enabling the operator to quickly and effectively navigate the video archives using systematic indexing making it possible to extract the information on the stream before compression to benefit from maximum image quality.